FreeWorkshop:AIimplementationTechniquesfromTheCloudtotheEdge

Workshop Objectives

Xilinx accelerates cloud-to-edge solutions

Focusing on Xilinx's cloud-to-edge FPGA acceleration solution, this topic will give you a deeper understanding of how to accelerate your cloud-to-edge applications with Xilinx FPGAs to optimize flexibility, performance and power consumption.

Deep learning from Cloud to Edge

It mainly describes how to quickly build a deep neural network based in inference logic in the cloud, to achieve specific classification or detection tasks, and how to deploy deep neural networks to terminals that are sensitive to computing power, cost, power consumption, etc., and how to and how to provide real-time responsiveness of the terminal.

Deep Learning Applications on Xilinx FPGAs with IBM ToolsSaves months of works compare to regular VHDL/Verilog handcoding! This topic mainly describes how to quickly implement the deep learning algorithm on the FPGA platform and verify the performance of the algorithm by means of IBM's model conversion tool and DeepRED platform. At the same time, the construction plan of the artificial intelligence laboratory and the supported research experiments will be introduced.